Abstract
Climate change and population growth are putting increasing pressure on global food security. The development of high-yielding varieties for important crops such as wheat is crucial to meet these challenges. The basis for this is extensive exploitation of beneficial genetic variation resting in genebanks around the world. Selecting suitable donor genotypes from the vast number of wheat accessions stored in genebanks is a difficult task and depends critically on the density of information on the performance of individual accessions. Therefore, this study aimed to access phenotypic data from the Czech genebank, storing over 13,000 wheat accessions. We curated and analyzed data on heading date, plant height, and thousand grain weight for more than one-third of all available accessions regenerated across 70 years. The data underwent analysis using a linear mixed model, revealing high quality of curated data with heritability reaching 99%. The raw data, but also derived data such as the best linear unbiased estimations, are now available for the wheat collection of the Czech genebank for research and breeding.